SoroushVahidi/scidocs huggingface dataset:
AVANT-GUARD: scalable and vigilant switch flow management in software-defined networks
(2013)

Among the leading reference implementations of the Software Defined Networking (SDN) paradigm is the OpenFlow framework, which decouples the control plane into a centralized application. In this paper, we consider two aspects of OpenFlow that pose security challenges, and we propose two solutions that could address these concerns. The first challenge is the inherent communication bottleneck that arises between the data plane and the control plane, which an adversary could exploit by mounting a "control plane saturation attack" that disrupts network operations. Indeed, even well-mined adversarial models, such as scanning or denial-of-service (DoS) activity, can produce more potent impacts on OpenFlow networks than traditional networks. To address this challenge, we introduce an extension to the OpenFlow data plane called "connection migration", which dramatically reduces the amount of data-to-control-plane interactions that arise during such attacks. The second challenge is that of enabling the control plane to expedite both detection of, and responses to, the changing flow dynamics within the data plane. For this, we introduce "actuating triggers" over the data plane's existing statistics collection services. These triggers are inserted by control layer applications to both register for asynchronous call backs, and insert conditional flow rules that are only activated when a trigger condition is detected within the data plane's statistics module. We present Avant-Guard, an implementation of our two data plane extensions, evaluate the performance impact, and examine its use for developing more scalable and resilient SDN security services.
Less-structured time in children's daily lives predicts self-directed executive functioning
(2014)

Executive functions (EFs) in childhood predict important life outcomes. Thus, there is great interest in attempts to improve EFs early in life. Many interventions are led by trained adults, including structured training activities in the lab, and less-structured activities implemented in schools. Such programs have yielded gains in children's externally-driven executive functioning, where they are instructed on what goal-directed actions to carry out and when. However, it is less clear how children's experiences relate to their development of self-directed executive functioning, where they must determine on their own what goal-directed actions to carry out and when. We hypothesized that time spent in less-structured activities would give children opportunities to practice self-directed executive functioning, and lead to benefits. To investigate this possibility, we collected information from parents about their 6-7 year-old children's daily, annual, and typical schedules. We categorized children's activities as "structured" or "less-structured" based on categorization schemes from prior studies on child leisure time use. We assessed children's self-directed executive functioning using a well-established verbal fluency task, in which children generate members of a category and can decide on their own when to switch from one subcategory to another. The more time that children spent in less-structured activities, the better their self-directed executive functioning. The opposite was true of structured activities, which predicted poorer self-directed executive functioning. These relationships were robust (holding across increasingly strict classifications of structured and less-structured time) and specific (time use did not predict externally-driven executive functioning). We discuss implications, caveats, and ways in which potential interpretations can be distinguished in future work, to advance an understanding of this fundamental aspect of growing up.
SECURITY ENHANCEMENT OF ADVANCED ENCRYPTION STANDARD (AES) USING TIME-BASED DYNAMIC KEY GENERATION
(2015)

Login is the first step which is conducted every time we access to a system and only granted to those who are entitled. Login is very important and it is a part of the security of a system. Registered user or guest and administrator are two kinds of users that have the privilege and access. Nowadays, wrongdoers are always on the dark side and frequently try to gain access to the system. To provide a better security, it is important to enhance the access mechanism and to evaluate the authentication process. Message-Digest 5 (MD5) is one of the algorithms that commonly used in the login system. Although it has been so popular, but the algorithm is still vulnerable to dictionary attacks and rainbow tables. In addition to the hash function algorithm, Advanced Encryption Standard (AES) algorithm alternatively can be the best choice in the login authentication process. This study is proposed to develop a dynamic key generation on the AES algorithm using the function of time. The experimental results obtained that AES key can be generated at random based on the value of the time when a user logs in with a particular active period. In this implementation, the security authentication becomes stronger because of changes in key generating chipertext changes for each encryption process. Based on the time as a valuable benchmark, the result shown that AES encryption-decryption process is relatively fast with a time average about 0.0023 s.
Efficiently solving dynamic Markov random fields using graph cuts
(2005)

In this paper, we present a fast new fully dynamic algorithm for the st-mincut/max-flow problem. We show how this algorithm can be used to efficiently compute MAP estimates for dynamically changing MRF models of labeling problems in computer vision, such as image segmentation. Specifically, given the solution of the max-flow problem on a graph, we show how to efficiently compute the maximum flow in a modified version of the graph. Our experiments showed that the time taken by our algorithm is roughly proportional to the number of edges whose weights were different in the two graphs. We test the performance of our algorithm on one particular problem: the object-background segmentation problem for video and compare it with the best known st-mincut algorithm. The results show that the dynamic graph cut algorithm is much faster than its static counterpart and enables real time image segmentation. It should be noted that our method is generic and can be used to yield similar improvements in many other cases that involve dynamic change in the graph
Blur-invariant copy-move forgery detection technique with improved detection accuracy utilising SWT-SVD
(2017)

Majority of the existing copy-move forgery detection algorithms operate based on the principle of image block matching. However, such detection becomes complicated when an intelligent adversary blurs the edges of forged region(s). To solve this problem, the authors present a novel approach for detection of copy-move forgery using stationary wavelet transform (SWT) which, unlike most wavelet transforms (e.g. discrete wavelet transform), is shift invariant, and helps in finding the similarities, i.e. matches and dissimilarities, i.e. noise, between the blocks of an image, caused due to blurring. The blocks are represented by features extracted using singular value decomposition (SVD) of an image. Also, the concept of colour-based segmentation used in this work helps to achieve blur invariance. The authors’ experimental results prove the efficiency of the proposed method in detection of copy-move forgery involving intelligent edge blurring. Also, their experimental results prove that the performance of the proposed method in terms of detection accuracy is considerably higher compared with the state-of-theart.
Automatic Service Discovery of IP Cameras over Wide Area Networks with NAT Traversal
(2012)

A novel framework for remote service discovery and access of IP cameras with Network address Translation (NAT) traversal is presented in this paper. The proposed protocol, termed STDP (Service Trader Discovery Protocol), is a hybrid combination of Zeroconf and SIP (Session Initial Protocol). The Zeroconf is adopted for the discovery and/or publication of local services; whereas, the SIP is used for the delivery of local services to the remote nodes. In addition, both the SIP-ALG (Application Layer Gateway) and UPnP (Universal Plug and Play)-IGD (Internet Gateway Device) protocols are used for NAT traversal. The proposed framework is well-suited for high mobility applications where the fast deployment and low administration efforts of IP cameras are desired.
WreckWatch: Automatic Traffic Accident Detection and Notification with Smartphones
(2011)

Traffic accidents are one of the leading causes of fatalities in the US. An important indicator of survival rates after an accident is the time between the accident and when emergency medical personnel are dispatched to the scene. Eliminating the time between when an accident occurs and when first responders are dispatched to the scene decreases mortality rates by 6%. One approach to eliminating the delay between accident occurrence and first responder dispatch is to use in-vehicle automatic accident detection and notification systems, which sense when traffic accidents occur and immediately notify emergency personnel. These in-vehicle systems, however, are not available in all cars and are expensive to retrofit for older vehicles. This paper describes how smartphones, such as the iPhone and Google Android platforms, can automatically detect traffic accidents using accelerometers and accoustic data, immediately notify a central emergency dispatch server after an accident, and provide situational awareness through photographs, GPS coordinates, VOIP communication channels, and accident data recording. This paper provides the following contributions to the study of detecting traffic accidents via smartphones: (1) we present a formal model for accident detection that combines sensors and context data, (2) we show how smartphone sensors, network connections, and web services can be used to provide situational awarenss to first responders, and (3) we provide empirical results demonstrating the efficacy of different approaches employed by smartphone accident detection systems to prevent false positives. J. White and H. Turner Dept. of Electrical and Computer Engineering Virginia Tech E-mail: {julesw,hturner0}@vt.edu C. Thompson, B. Dougherty, and D.C. Schmidt Dept. of Electrical Engineering and Computer Science Vanderbilt University E-mail: {cthompson,briand,schmidt}@dre.vanderbilt.edu
An IT Balance Scorecard Design under Service Management Philosophy
(2012)

The present study proposes a design for an Information Technology Balanced Scorecard (IT BSC) that integrates with business and environment and balances and optimizes deployment and control of the Information Technology strategy. This Strategic and Tactical IT Planning model enhances IT's role in obtaining and measuring its contribution to business value: optimizing IT operational efficiency or proposing new business ideas with a high IT component. The proposed model stimulates innovation in each of the parts of the IT Services lifecycle, is based on IT Service Management best practices and uses ideas from the ITIL v3 standard.
Clustering Based Approach for Customers ’ Classification from Electrical Distribution Systems
(2015)

The paper presents a clustering based approach for consumers’ classification in representative categories characterized by typical load profiles. For determination of the consumption categories, every customer must be characterized by the following primary information: daily (monthly) energy consumption, average load and peak load. The used database contains the daily load curves corresponding to the small customers from a rural distribution system from Romania. The obtained results it demonstrated that the proposed approach can be used with the success in building specific tariff structures of the customers or in the optimal operation and planning of distribution systems.
The Media ' s Influence on Body Image Disturbance and Eating Disorders : We ' ve Reviled Them , Now Can We Rehabilitate Them ?
(1999)

Survey, correlational, randomized control, and covariance structure modeling investigations indicate that the media are a significant factor in the development and maintenance of eating and shape-related disorders. One specific individual difference variable, intemalization of societal pressures regarding prevailing standards of attractiveness, appears to moderate or even mediate the media's effects on women's body satisfaction and eating dysfunction. Problematic media messages inherent in existing media portrayals of eating disorders are apparent, leading researchers to pinpoint intervention strategies that might counteract such viewpoints. Social activism and social marketing approaches are suggested as methods for fighting negative media messages. The media itself is one potential vehicle for communicating productive, accurate, and deglamorized messages about eating and shape-related disorders.
Statistical Edge Detection: Learning and Evaluating Edge Cues
(2003)

We formulate edge detection as statistical inference. This statistical edge detection is data driven, unlike standard methods for edge detection which are model based. For any set of edge detection filters (implementing local edge cues) we use pre-segmented images to learn the probability distributions of filter responses conditioned on whether they are evaluated on or off an edge. Edge detection is formulated as a discrimination task specified by a likelihood ratio test on the filter responses. This approach emphasizes the necessity of modeling the image background (the off-edges). We represent the conditional probability distributions non-parametrically and learn them on two different datasets of 100 (Sowerby) and 50 (South Florida) images. Multiple edges cues, including chrominance and multiple-scale, are combined by using their joint distributions. Hence this cue combination is optimal in the statistical sense. We evaluate the effectiveness of different visual cues using the Chernoff information and Receiver Operator Characteristic (ROC) curves. This shows that our approach gives quantitatively better results than the Canny edge detector when the image background contains
Single-Fed Low Profile Broadband Circularly Polarized Stacked Patch Antenna
(2014)

A simple technique is developed in this communication to increase the axial ratio (AR) bandwidth and achieve good impedance matching of a single-fed low profile circularly polarized (CP) stacked patch antenna. The proposed antenna is composed of a driven patch layer and a parasitic patch layer. The driven patch layer consists of a truncated main patch, a parasitic patch and a probe feeding structure while the stacked patch layer is comprised of five patches. The proposed antenna combines the attractive features such as low profile, wide impedance and AR bandwidths, high gain as well as easiness of design, manufacture and integration. The antenna operating at 6 GHz band is designed and fabricated on an FR4 substrate and the overall volume is 0.8 λ0 ×0.8 λ0 ×0.09 λ0. Measured results show that the antenna achieves an impedance bandwidth of more than 30% for dB, a 3-dB AR bandwidth of about 20.7%, and a gain level of over 7.9 dBi within the 3-dB AR bandwidth.
Man-At-The-End attacks: Analysis, taxonomy, human aspects, motivation and future directions
(2015)

Man-At-The-End (MATE) attacks and fortifications are difficult to analyze, model, and evaluate predominantly for three reasons: firstly, the attacker is human and, therefore, utilizes motivation, creativity, and ingenuity. Secondly, the attacker has limitless and authorized access to the target. Thirdly, all major protections stand up to a determined attacker till a certain period of time. Digital assets range from business to personal use, from consumer devices to home networks, the public Internet, the cloud, and the Internet of Things – where traditional computer and network security are inadequate to address MATE attacks. MATE is fundamentally a hard problem. Much of the extant focus to deal with MATE attacks is purely technical; though security is more than just a technical issue. The main objective of the paper is to mitigate the consequences of MATE attacks through the human element of security and highlight the need for this element to form a part of a holistic security strategy alongside the necessary techniques and technologies. This paper contributes by taking software protection (SP) research to a new realm of challenges. Moreover, the paper elaborates the concept of MATE attacks, the different forms, and the analysis of MATE versus insider threats to present a thematic taxonomy of a MATE attack. The ensuing paper also highlights the fundamental concept of digital assets, and the core protection mechanisms and their qualitative comparison against MATE attacks. Finally, we present state-of-the-art trends and cutting-edge future research directions by taking into account only the human aspects for young researchers and professionals. & 2014 Elsevier Ltd. All rights reserved.
A multiperiod set covering location model for dynamic redeployment of ambulances
(2008)

Emergency medical service (EMS) providers continually seek ways to improve system performance particularly the response time to incidents. The demand for ambulances fluctuate throughout the week, depending on the day of week, and even the time of day, therefore EMS operators can improve system performance by dynamic relocation/redeployment of ambulances in response to fluctuating demand patters. The objective of the model is to determine the minimum number of ambulances and their locations for each time cluster in which significant changes in demand pattern occur while meeting coverage requirement with a predetermined reliability. The model is further enhanced by calculating ambulance specific busy probabilities and validated by a comprehensive simulation model. Computational results on experimental data sets and data from an EMS agency are provided. 2006 Elsevier Ltd. All rights reserved.
Static Scheduling of Synchronous Data Flow Programs for Digital Signal Processing
(1987)

Large grain data flow (LGDF) programming is natural and convenient for describing digital signal processing (DSP) systems, but its runtime overhead is costly in real time or cost-sensitive applications. In some situations, designers are not willing to squander computing resources for the sake of programmer convenience. This is particularly true when the target machine is a programmable DSP chip. However, the runtime overhead inherent in most LGDF implementations is not required for most signal processing systems because such systems are mostly synchronous (in the DSP sense). Synchronous data flow (SDF) differs from traditional data flow in that the amount of data produced and consumed by a data flow node is specified a priori for each input and output. This is equivalent to specifying the relative sample rates in signal processing system. This means that the scheduling of SDF nodes need not be done at runtime, but can be done at compile time (statically), so the runtime overhead evaporates. The sample rates can all be different, which is not true of most current data-driven digital signal processing programming methodologies. Synchronous data flow is closely related to computation graphs, a special case of Petri nets. This self-contained paper develops the theory necessary to statically schedule SDF programs on single or multiple processors. A class of static (compile time) scheduling algorithms is proven valid, and specific algorithms are given for scheduling SDF systems onto single or multiple processors.
Contribution of obesity and abdominal fat mass to risk of stroke and transient ischemic attacks.
(2008)

BACKGROUND AND PURPOSE
Waist circumference has been shown to be a better predictor of cardiovascular risk than body mass index (BMI). Our case-control study aimed to evaluate the contribution of obesity and abdominal fat mass to the risk of stroke and transient ischemic attacks (TIA).


METHODS
We recruited 1137 participants: 379 cases with stroke/TIA and 758 regional controls matched for age and sex. Associations between different markers of obesity (BMI, waist-to-hip ratio, waist circumference and waist-to-stature ratio) and risk of stroke/TIA were assessed by using conditional logistic regression adjusted for other risk factors.


RESULTS
BMI showed a positive association with cerebrovascular risk which became nonsignificant after adjustment for physical inactivity, smoking, hypertension, and diabetes (odds ratio 1.18; 95% CI, 0.77 to 1.79, top tertile versus bottom tertile). Markers of abdominal adiposity were strongly associated with the risk of stroke/TIA. For the waist-to-hip ratio, adjusted odds ratios for every successive tertile were greater than that of the previous one (2nd tertile: 2.78, 1.57 to 4.91; 3rd tertile: 7.69, 4.53 to 13.03). Significant associations with the risk of stroke/TIA were also found for waist circumference and waist-to-stature ratio (odds ratio 4.25, 2.65 to 6.84 and odds ratio 4.67, 2.82 to 7.73, top versus bottom tertile after risk adjustment, respectively).


CONCLUSIONS
Markers of abdominal adiposity showed a graded and significant association with risk of stroke/TIA, independent of other vascular risk factors. Waist circumference and related ratios can better predict cerebrovascular events than BMI.
Firmaster: Analysis Tool for Home Router Firmware
(2018)

As the Internet has changed the way people communicate with each other in everyday life, the number of home Wi-Fi access routers has grown up significantly over the past few years. However, the security of routers used in every household is still in the low level. The common vulnerabilities in routers can be easily exploited by an attacker in order to obtain user’s sensitive information or even compromise the devices to be a part of the botnet network. Therefore, we developed one-stop service firmware analysis tool that can perform both static and dynamic analysis for the router firmware called “Firmaster”. textbfThe program is operated under graphical user interface (GUI) of Qt creator running on the Ubuntu Linux machine. textbfVulnerabilities of firmware analyzed by Firmaster program are based on OWASP’s Top 10 IoT Vulnerabilities 2014. Firmaster contains seven main functions: password cracking, SSL scanning, web static analysis, firmware update analysis, web dynamic analysis, port scanning and the summary report.
An Approach Based on Tree Kernels for Opinion Mining of Online Product Reviews
(2010)

Opinion mining is a challenging task to identify the opinions or sentiments underlying user generated contents, such as online product reviews, blogs, discussion forums, etc. Previous studies that adopt machine learning algorithms mainly focus on designing effective features for this complex task. This paper presents our approach based on tree kernels for opinion mining of online product reviews. Tree kernels alleviate the complexity of feature selection and generate effective features to satisfy the special requirements in opinion mining. In this paper, we define several tree kernels for sentiment expression extraction and sentiment classification, which are subtasks of opinion mining. Our proposed tree kernels encode not only syntactic structure information, but also sentiment related information, such as sentiment boundary and sentiment polarity, which are important features to opinion mining. Experimental results on a benchmark data set indicate that tree kernels can significantly improve the performance of both sentiment expression extraction and sentiment classification. Besides, a linear combination of our proposed tree kernels and traditional feature vector kernel achieves the best performances using the benchmark data set.